New answers tagged matlab
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D.T Kalman filter time update equations (predict) with initial estimates for $\hat{x}_k$ and $P_{k}$
Project the state ahead: $\hat{x}^-_{k+1} = F\hat{x}_{k}+Bu_{k}$
Project the error covariance ahead: $P^-_{k+1} = FP_{k}F^T+Q$
Measurement equations (correct)
Compute the Kalman gain: $K_{k+1} = P^-_{k+1}C^T(CP^-_{k+1}C^T+R)^{-1}$
Update estimate with ...
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